Dynamic allocation and coordination of auto-navigating vehicles and selectors

ABSTRACT

Dynamic allocation and coordination of auto-navigating vehicles uses robotic vehicles and centrally dispatched roaming order selectors to create a significantly more efficient, yet flexible, approach to picking goods within a warehouse. Robotic vehicles are configured to be loaded with goods from pick faces to fill orders. Each robotic vehicle follows a route that includes appropriate pick face locations. The robotic vehicles navigate from pick face to pick face where particular goods are located. Order selectors are dynamically and independently dispatched to meet the robotic vehicles at their pick face locations to load goods. Movement of the order selectors is orchestrated to increase efficiency in the order filling process within the warehouse.

RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 16/892,549, filed Jun. 4, 2020, entitled DynamicAllocation and Coordination of Auto-Navigating Vehicles and Selectors,now U.S. Publication No.: 2020/0387154, published Dec. 10, 2020, whichclaims benefit of U.S. Provisional Application No. 62/856,865, filedJun. 4, 2019, and entitled DYNAMIC ALLOCATION AND COORDINATION OFAUTO-NAVIGATING VEHICLES AND SELECTORS, which is hereby incorporated byreference in its entirety.

FIELD OF INTEREST

The present inventive concepts relate to the field of systems andmethods in the field of storage facility management, and moreparticularly to systems and methods involved in case picking orselection of goods in a warehouse environment.

BACKGROUND

A storage facility is a facility primarily used for storage of goods forcommercial purposes, such as a warehouse. The storage is generallyintended to be temporary, as such goods ultimately may be intended for aretailer, consumer or customer, distributor, transporter or othersubsequent receiver. A warehouse can be a standalone facility, or can bepart of a multi-use facility. Thousands of types of items can be storedin a typical warehouse. The items can be small or large, individual orbulk. It is common to load items on a pallet for transportation, and thewarehouse may use pallets as a manner of internally transporting andstoring items.

A well-run warehouse is well-organized and maintains an accurateinventory of goods. Goods can come and go frequently, throughout theday, in a warehouse. In fact, some large and very busy warehouses workthree shifts, continually moving goods throughout the warehouse as theyare received or needed to fulfill orders. Shipping and receiving areas,which may be the same area, are the location(s) in the warehouse wherelarge trucks pick-up and drop-off goods. The warehouse can also includea staging area—as an intermediate area between shipping and receivingand storage aisles within the warehouse where the goods are stored. Thestaging area, for example, can be used for confirming that all items onthe shipping manifest were received in acceptable condition. The stagingarea can also be used to build orders and pallets to fulfill orders thatare to be shipped.

Goods in a warehouse tend to be moved in one of two ways, either bypallet or by cart (or trailer). A pallet requires a pallet transport formovement, such as a pallet jack, pallet truck, forklift, or stacker. Astacker is a piece of equipment that is similar to a fork lift, but canraise the pallet to significantly greater heights, e.g., for loading apallet on a warehouse shelf. A cart requires a tugger (or “towtractor”), which enables a user to pull the cart from place to place.

A pallet transport can be manual or motorized. A traditional pallet jackis a manually operated piece of equipment, as is a traditional stacker.When a pallet transport is motorized, it can take the form of a poweredpallet jack, pallet truck, or forklift (or lift truck). A motorizedstacker is referred to as a power stacker. A motorized pallet jack isreferred to as a powered pallet jack, which an operator cannot ride, butwalks beside. A pallet truck is similar to a powered pallet jack, butincludes a place for an operator to stand.

As with motorized pallet transports, a tugger can be in the form of adrivable vehicle or in the form of a powered vehicle along the side ofwhich the operator walks. In either form, a tugger includes a hitch thatengages with a companion part on the cart, such as a sturdy and rigidring or loop.

Various types of vehicles exist that can navigate without directreliance on a human driver, such as autonomous mobile robots (AMRs),automatic guided vehicle (AGV, vision guided vehicles (VGV), andautonomous guided carts (AGCs), as examples. For purposes of brevity,such vehicles will be collectively referred to as AGVs. AGV forms ofpallet trucks and powered tuggers exist. An AGV is a mobile robot thatfollows markers or wires in the floor, or uses vision or lasers to makeits way without direct or remote control by an operator. They are mostoften used in industrial applications to move materials around amanufacturing facility or a warehouse, such as in the case of AGVforklifts and AGV tuggers.

FIG. 1 is a simplified diagram of a storage facility 100 in the form ofa warehouse. Warehouse 100 includes a shipping & receiving area 110 anda staging area 112. A loading dock may be provided, where goods can beloaded on and unloaded from trucks 116. In the staging area, pallets 114are shown, and may be loaded with warehouse goods to fulfill an order.When a pallet 114 is loaded with goods, it can remain in the stagingarea 112 or shipping and receiving area 110 until it is ready forloading on a truck 116. In which case, the pallet 114 is moved to theshipping & receiving area 110 and then onto the truck 116.

Warehouse 100 includes a plurality of aisles and storage spaces(collectively aisles 120) where the goods are intended to be stored inan orderly manner. Additionally, zones can be defined in a warehouse—asa means for categorizing areas within a warehouse. A zone can be definedfor an aisle, group of aisles, portion of an aisle, or variouscombinations thereof. In FIG. 1 , several zones are defined, includingzones A-E.

When one or more orders is to be filled, a “pick list” is generated,which tells an order selector (or picker) which aisles to go to andwhich goods to pick. Pallet transports or tuggers and carts(collectively pallet transport 130) are sent through warehouse 100 withthe order selector to “pick” cases, totes, cartons, or other forms ofcontainers of goods (collectively “cases” herein). A “tote” is acontainer that is used to fill an order on a piece-by-piece basis, wherethe pieces are individual goods or groupings of relatively small goods.The goods are arranged in aisles 120, and the same goods are arranged asa “pick face.” A “pick face” is a location, usually a two-dimensionalfacing or area, in a warehouse or stock area that is designated for thestorage of one or more products and is accessible by an order selectorfor order filling. The cases are loaded on pallet transport 130 andbrought to either the staging area 112 or shipping & receiving area 110.

FIG. 2 is a block diagram of a front view of an aisle and pick facesthat can exist in aisle 120. In this view, four pick faces are shown,i.e., pick faces 0, 1, 5, and 6. Pick faces 0 and 1 are located on ashelf and pick faces 5 and 6 are at ground level. Each pick face isdefined for a certain product. For example, pick face 0 shows 6 cases ofthe same product in FIG. 2 .

There are different approaches to arranging products in a warehouse,which is referred to as “slotting.” Slotting is viewed by many to be thekey to the efficiency of the warehouse operation, where the highestpossible “pick rates” are desired. Generally speaking, “pick rate” meansthe number of cases or units picked per unit of time perpicker/selector.

One common approach to slotting products is to use item velocity.Generally, the more popular a product is, the higher its itemvelocity—the faster or more frequently it moves in and out of thewarehouse. When slotting by item velocity, it is typical to keep theproducts with the highest item velocities in zones closest to theshipping & receiving 110 area (or staging area 112). Meanwhile, itemswith the lowest item velocities tend to be in zones furthest away.Slotting by item velocity can reduce travel time within a warehouse whenfilling orders. Reducing travel time is an important factor inincreasing pick rates—so it is considered quite advantageous to slot byitem velocity.

Another way to slot products in a warehouse is by productcategories—grocery stores tend to use this approach. For example, paperproducts may be a product category. One or more product categories mayexist within a zone. To increase efficiency with this type of productslotting, it may be advantageous to pick all products from a categorythat are needed to fill multiple orders—and then put the orders togetherin the staging area 112.

Still another slotting approach is “chaos” slotting, where slots areassigned quasi-randomly, with the objective of spreading a given goodthroughout the warehouse, thus allowing multiple nonconflictingsimultaneous picks to occur. This makes more sense for an entity thathas so many SKUs that fast movers are not a great differentiator.

There are many different methods for filling the order. The methodchosen will typically depend on the way the products are slotted andwhether or not cases are being picked versus individual products, e.g.,a case of aspirin versus 12 bottles of aspirin. Some of the most commonorder picking methods are:

-   -   Single order picking—Each order selector selects a customer        order and picks it to completion.    -   Batch picking—An order selector fills several orders at a time        in order to reduce the amount of time spent traveling.    -   Pick and pass—Each order selector concentrates on his own area        or zone and orders pass (mechanically or manually) from one        order selector to the next.    -   Zone picking with aggregation on the shipping dock—Different        zones send one or more cases to shipping for each order, and the        cases from each zone are palletized together on the shipping        dock.    -   Zone picking with aggregation at packing—Each zone sends one or        more totes to a packing area (e.g., staging 112 in FIG. 1 ) with        its portion of the order. At packing, all totes for an order are        consolidated, and outbound cartons (e.g., boxes) are packed with        the goods from the totes for a particular order.    -   Zone picking without aggregation—Each zone fills its carton for        the order, and these are sent directly to the shipping trailer.    -   Unit sortation—Order selectors pull batches of product from        their zones that are then sorted to the order by a tilt tray or        cross-belt sorter.

The appropriateness of a particular order filling method will alsodepend on its impact on pick rates. The higher the overall pick rate,the more efficient and cost effective the warehouse.

Referring again to FIG. 1 , a warehouse management system, or WMS, 140is a key part of the supply chain and primarily aims to control themovement and storage of goods within warehouse 100. The WMS can processtransactions associated with the movement of goods into, out of, andwithin the warehouse, including shipping, receiving, putaway andpicking. “Putaway” generally refers to moving goods into the warehouseor storage area at their designated storage locations, e.g., zones andpick faces.

The WMS can provide a set of computerized procedures to handle thetracking and management of goods at a warehouse, model and manage thelogical representation of the physical storage facilities (e.g. rackingetc.), and enable a seamless link to order processing and logisticsmanagement in order to pick, pack and ship product out of the warehouse.Warehouse management systems can be standalone systems, or modules of anenterprise resource management system or supply chain execution suite.Orders can be electronically received by a WMS or manually input. Picklists can be automatically or manually generated from the order, whichcan include route optimization performed by the WMS.

When picking cases to fill orders, it is typical to use pallettransports 130 that are navigated through the warehouse 100 to pickfaces within zones to retrieve the necessary product cases. When doingso, the pallet transport 130 is navigated under the control of the orderselector. That is, the order selector looks at a first/next item on apick list, which indicates the aisle, pick face, and (optionally) zonewhere the corresponding product is located. The order selector drivesthe pallet transport to the pick face, and loads the appropriate numberof cases on the pallet (or cart). This is done for each product on thepick list, until the order selector has worked completely through thepick list.

If the order selector is only picking for a particular zone, he canbring the pallet transport to the next zone and hand it off to the nextorder selector to continue working down the pick list. If the orderselector is picking the complete pick list, then he can drive the pallettransport to the shipping & receiving area 110 or staging area 112 whenthe order is complete.

SUMMARY OF INVENTION

Provided are a system and method for coordinating the motions andactions of two disparate classes of actors that need to coordinate atvarying meeting points in time/space.

In various embodiments, the system and method could include dynamicallocation and coordination of auto-navigating vehicles. The dynamicallocation and coordination of auto-navigating vehicles uses roboticvehicles and centrally dispatched roaming order selectors to create asignificantly more efficient, yet flexible, approach to picking goodswithin a warehouse. Robotic vehicles are configured to be loaded withgoods from pick faces to fill orders. Each robotic vehicle follows aroute that includes appropriate pick face locations. The roboticvehicles navigate from pick face to pick face where particular goods arelocated. Order selectors are dynamically and independently dispatched tomeet the robotic vehicles at their pick face locations to load goods.Movement of the order selectors is orchestrated to increase efficiencyin the order filling process within the warehouse.

In accordance with aspects of the present invention, provided is anautomated case picking method. The method comprises providing arepresentation of a storage facility and pick lists in an electronicmemory, each pick list providing identifications of items to be pickedfrom a plurality of different pick locations to fulfill an order,wherein each pick location is designated for storage of one or moreproducts. For each pick list, electronically generating a route withinthe storage facility comprising the pick locations for the pick list.The method includes electronically transmitting routes to a plurality ofrobotic vehicles, each robotic vehicle configured to auto-navigate toeach pick location on a received route, electronically trackinglocations of the robotic vehicles and a plurality of mobile selectorunits, and electronically determining and communicating navigationinstructions to the plurality of mobile selector units based, at leastin part, on locations of the mobile selector units and the roboticvehicles and next pick locations of the robotic vehicle routes. Thenavigation instructions received by each mobile selector unit areconfigured to direct the mobile selector unit to a next pick location ona route of one of the robotic vehicles and each mobile selector unit canservice routes of more than one of the robotic vehicles. Further, eachvehicle may be serviced by one or more mobile selector units.

The storage facility can be a warehouse.

In various embodiments, the method can further comprise a warehousedatabase having the representation of the storage facility and the picklists in an electronic memory.

In various embodiments, the method can further comprise at least oneprocessor accessing the warehouse database and electronically generatingone or more of the routes.

In various embodiments, the method can further comprise the at least oneprocessor electronically transmitting the routes to the plurality ofrobotic vehicles.

In various embodiments, the method can further comprise the at least oneprocessor electronically tracking locations of the robotic vehicles andthe mobile selector units.

In various embodiments, the method can further comprise the at least oneprocessor electronically determining and communicating navigationinstructions to the plurality of mobile selector units.

In various embodiments, the method can further comprise including the atleast one processor wirelessly communicating the navigation instructionsto the plurality of selector units.

In various embodiments, the method can further comprise the at least oneprocessor dynamically determining and wirelessly communicating nextnavigation instructions to the plurality of selector units based, atleast in part, on changes in the locations of the mobile selector unitsand the robotic vehicles.

In various embodiments, the method can further comprise therepresentation of the storage facility comprising a plurality of zonesand determining the navigation instructions for the robotic vehicles isindependent of the zones.

In various embodiments, the method can further comprise, after themobile selector unit navigates to the next pick location, the mobileselector unit receiving instructions to navigate to a new next picklocation in a different zone.

In various embodiments, the method can further comprise the mobileselector units are configured for wireless communication.

In various embodiments, the method can further comprise the plurality ofmobile selector units includes handheld mobile terminals.

In various embodiments, the method can further comprise the plurality ofmobile selector units includes mobile phones, tablets, phablets,wearable/augmented reality devices (e.g. Microsoft HoloLens or GoogleGlass), Bar code scanners (with some level of onboard display & logic),voice-interaction-only devices (e.g. Vocollect belt pack and headset),gesture-interaction-only devices, and/or a combination of two or morethereof.

In various embodiments, the method can further comprise the mobileselector units include one or more user interface devices, including atleast one pick-complete device that, when actuated, generates apick-complete signal indicating that loading of products from a picklocation to the robotic vehicle has been completed and the roboticvehicle is clear to proceed to a new next pick location on its route.

In various embodiments, the method can further comprise the mobileselector unit communicating the pick-complete signal to the roboticvehicle.

In various embodiments, the method can further comprise the mobileselector unit communicating the pick-complete signal to the at least oneprocessor.

In various embodiments, determining the navigation instructions includesprocessing the locations of the mobile selector units and roboticvehicles and the next pick locations to reduce travel distances and/ortimes of the mobile selector units.

In various embodiments, determining the navigation instructions includesprocessing the locations of the mobile selector units and roboticvehicles and the next pick locations to manage fatigue of one or more ofthe selector units, maximize warehouse throughput, and/or meetpredetermined deadlines, e.g., provided by the WMS.

In various embodiments, determining the navigation instructions includesprocessing the locations of the mobile selector units and roboticvehicles and the next pick locations for congestion avoidance.

In various embodiments, determining the navigation instructions isfurther based on an estimated time of arrival to the next pick locationsby the robotic vehicles and/or the selector units.

In various embodiments, the plurality of robotic vehicles can include atugger, a forklift, a high-lift or powered stacker, and/or a pallettruck.

The robotic vehicle can be a tugger.

The robotic vehicle can be a forklift.

The robotic vehicle can be a high-lift or powered stacker.

The robotic vehicle can be a pallet truck and the load platform can be apallet. In some embodiments, the load platform could also be some sortof pallet fixture such that the pallet can be dropped on top of thepallet jack forks, e.g. if interacting with forklifts at the start andend of a picklist.

The robotic vehicle can be a tugger and the load platform can be a cart.Vehicles where the load rests on the vehicle itself rather than beingpulled behind it.

In accordance with another aspect of the inventive concepts, provided isan electronic travel management method. The method comprises providing amanagement system in communication with a plurality of robotic vehiclesand a plurality of mobile selector units, each robotic vehicle executinga route and each mobile selector unit having a wireless communicationdevice, wherein each route comprises a pick list identifying picklocations of items to be picked to fulfill an order. The method includesthe management system tracking locations and movement of the roboticvehicles along their respective routes, tracking locations of the mobileselector units, and directing the mobile selector units to futurelocations of the robotic vehicles based on locations of the roboticvehicles, routes of the robotic vehicles, and locations of the mobileselector units. Future locations of the robotic vehicles include futurepick locations of the respective robotic vehicle routes.

In various embodiments, directing the mobile selector units includeselectronically determining and wirelessly communicating navigationinstructions to the mobile selector units.

In various embodiments, the method includes the management systeminferring a location of at least one of the mobile selector units fromat least one of a last known pick location, a next known pick location,and an estimate of mobile selector travel speed and/or past measurementsof mobile selector travel speed.

In various embodiments, the routes are within a storage environment andthe management system further comprises an electronic representation ofthe storage environment and the pick lists and wherein directing themobile selector units is further based on the electronic representationof the storage environment and the pick lists.

In various embodiments, the electronic representation of the storageenvironment comprises a plurality of zones and the directing of themobile selector units includes providing navigation instructions for atleast one of the mobile selector unit to travel among plural zones.

In various embodiments, the electronic representation of the storageenvironment comprises a plurality of zones and the directing of themobile selector units includes providing navigation instructions for themobile selector units constrains travel of at least one mobile selectorunit within a single zone.

In various embodiments, the method further includes, after directing amobile selector unit to navigate to a pick location on a route of afirst robotic vehicle, the management system directing mobile selectorunit to navigate to a next pick location on a different route of asecond robotic vehicle.

In various embodiments, the next pick location is in the same zone asthe pick location of the first robotic vehicle.

In various embodiments, the next pick location is in a different zonethan the pick location of the first robotic vehicle.

In various embodiments, the plurality of robotic vehicles includes atugger, forklift, high-lift, and/or pallet truck.

In various embodiments, at least one of mobile selector units includes ahandheld mobile terminal.

In various embodiments, the handheld mobile terminal is chosen from agroup consisting of: mobile phones, voice-only devices,augmented-reality devices, barcode scanners, tablets, and/or phablets.

In various embodiments, the mobile selector units include one or moreuser interface devices, including at least one pick-complete devicethat, when actuated, generates a pick-complete signal indicating thatloading of products from a pick location to a robotic vehicle has beencompleted and the robotic vehicle is clear to proceed to a next picklocation on its route.

In various embodiments, the method includes the mobile selector unitcommunicating the pick-complete signal to the robotic vehicle.

In various embodiments, the method includes the mobile selector unitcommunicating the pick-complete signal to the management system.

In various embodiments, directing the mobile selector units includes themanagement system determining navigation instructions by processing thelocations of the mobile selector units and robotic vehicles and thesubsequent pick locations to reduce travel distances and/or times of themobile selector units.

In various embodiments, directing the mobile selector units includes themanagement system determining navigation instructions by processing thelocations of the mobile selector units and robotic vehicles and thesubsequent pick locations for congestion avoidance.

In various embodiments, directing the mobile selectors units includesdetermining navigation instructions further based on an estimated timeof arrival to a next pick location by at least one robotic vehicleand/or at least one mobile selector units.

In accordance with another aspect of the inventive concepts, provided isan electronic travel management system. The system comprises one or moreprocessors, logic and memory devices, and wireless communication devicescooperatively coupled together; and travel management logic embodied inlogic and memory devices. The travel management logic is executableunder the control of the one or more processors to communicate with aplurality of autonomous vehicles each executing a route, communicatewith a plurality of mobile selectors, each having a wireless mobileselector communication device, track locations and movement of theautonomous vehicles along their respective routes, track locations ofthe mobile selector communication devices, and direct the mobileselector communication devices to future locations of the autonomousvehicles based on locations of the autonomous vehicles, routes of theautonomous vehicles, and locations of the mobile selector devices.

In accordance with another aspect of the inventive concepts, provided isan electronic travel management system. The system comprises one or moreprocessors, logic and memory devices, and wireless communication devicescooperatively coupled together; and travel management logic embodied inlogic and memory devices. The travel management logic is executableunder the control of the one or more processors to communicate with aplurality of autonomous vehicles each executing a route, communicatewith a plurality of mobile selectors, each having a wireless mobileselector communication device, track locations and movement of theautonomous vehicles along their respective routes, track locations ofthe mobile selector communication devices, and orchestrate travel of themobile selector communication devices and/or the autonomous vehiclesbased on locations of the autonomous vehicles, routes of the autonomousvehicles, and locations of the mobile selector devices.

In various embodiments, the system can be configured to generatenavigation instructions to the mobile selector units to direct and/ororchestrate travel.

In various embodiments, system can be configured to reduce traveldistances and/or times of the mobile selector units and/or theautonomous vehicles to direct and/or orchestrate travel.

In various embodiments, system can be configured to perform congestionavoidance analysis to direct and/or orchestrate travel of the mobileselector units and/or autonomous vehicles.

In various embodiments, system can be configured to estimate time ofarrival to a next location by the mobile selector units and/or theautonomous vehicles to direct and/or orchestrate travel.

In various embodiments, one or more of the routes comprises a pluralityof pick faces and the system is configured to wirelessly direct at leastone mobile selector communication device to a next pick face of a routefor one or more of the autonomous vehicles.

In various embodiments, system can be further configured to generate oneor more of the routes and transmit the routes to one or more of theautonomous vehicles.

In various embodiments, system can be further configured to infer thelocations of the mobile selector units from at least one of last knownpick, next known pick, and an estimate of mobile selector travel speedand/or past measurements of mobile selector travel speed.

In various embodiments, system can be further configured toelectronically determine and communicate navigation instructions to theplurality of mobile selector units.

In various embodiments, system can be further configured to dynamicallydetermine and wirelessly communicate next navigation instructions to theplurality of mobile selector units based, at least in part, on changesin the locations of the mobile selector units and the autonomousvehicles.

In various embodiments, wherein the routes of the autonomous vehiclespass through a plurality of predetermined zones, and

travel of at least one of the mobile selector units is confined by thesystem to a subset of the zones.

In various embodiments, wherein the travel of at least one of the mobileselector units is confined by the system to a single zone from aplurality of zones.

In various embodiments, wherein the plurality of autonomous vehiclesincludes a tugger, forklift, high-lift, and/or pallet truck.

In various embodiments, wherein the plurality of mobile selector unitsincludes handheld mobile terminals.

In various embodiments, wherein the plurality of mobile selector unitsincludes at least one mobile phones, voice-only devices,augmented-reality devices, barcode scanners, tablets, and/or phablets.

In various embodiments, wherein the plurality of mobile selector unitsincludes vehicle-based mobile terminals.

In various embodiments, wherein at least one of the mobile selectorunits includes one or more user interface devices that outputs a nextlocation and/or travel path to the next location for the mobile selectorunit.

In various embodiments, wherein at least one of the mobile selectorunits includes at least one pick-complete device that, when actuated,generates a pick-complete signal indicating that loading of productsfrom a pick location to the autonomous vehicle has been completed andthe autonomous vehicle is clear to proceed to a new next pick locationon its route.

In various embodiments, wherein the mobile selector unit is configuredto communicate the pick-complete signal to the autonomous vehicle.

In various embodiments, wherein the mobile selector unit is configuredto communicate the pick-complete signal to the system.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become more apparent in view of the attacheddrawings and accompanying detailed description. The embodiments depictedtherein are provided by way of example, not by way of limitation,wherein like reference numerals refer to the same or similar elements.In the drawings:

FIG. 1 is a block diagram of a simplified warehouse.

FIG. 2 is a block diagram of a front view of an aisle and pick faces.

FIG. 3 is a block diagram of an embodiment of robotic vehicle modulesthat enable case picking, in accordance with aspects of the presentinvention.

FIGS. 4A and 4B are front views of an embodiment of pick face listdisplays, in accordance with aspects of the present invention.

FIG. 5 is a flowchart depicting an embodiment of a method of pickingcases with robotic vehicle assistance, in accordance with aspects of thepresent invention.

FIG. 6 is a flowchart depicting an embodiment of a method of pickingcases, in accordance with aspects of the present invention.

FIG. 7 is a flowchart depicting an embodiment of a method of pickingcases using zones and robotic vehicle assistance, in accordance withaspects of the present invention.

FIG. 8 is a flowchart depicting an embodiment of a method of dynamicallocation and coordination of auto-navigating vehicles where orderselectors are dynamically deployed to pick locations, in accordance withaspects of the present invention.

FIG. 9 is a diagram of a warehouse that comprising a system and a methodfor the dynamic allocation and coordination of auto-navigating vehicles,in accordance with aspects of the present invention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENT

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, these elements should notbe limited by these terms. These terms are used to distinguish oneelement from another, but not to imply a required sequence of elements.For example, a first element can be termed a second element, and,similarly, a second element can be termed a first element, withoutdeparting from the scope of the present invention. As used herein, theterm “and/or” includes any and all combinations of one or more of theassociated listed items.

It will be understood that when an element is referred to as being “on”or “connected” or “coupled” to another element, it can be directly on orconnected or coupled to the other element or intervening elements may bepresent. In contrast, when an element is referred to as being “directlyon” or “directly connected” or “directly coupled” to another element,there are no intervening elements present. Other words used to describethe relationship between elements should be interpreted in a likefashion (e.g., “between” versus “directly between,” “adjacent” versus“directly adjacent,” etc.).

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a,” “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises,”“comprising,” “includes” and/or “including,” when used herein, specifythe presence of stated features, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, steps, operations, elements, components, and/or groupsthereof.

FIG. 3 is a block diagram of an embodiment of a robotic vehicle 130 andvarious robotic vehicle modules 300 that can be used to enable casepicking, in accordance with aspects of the disclosure. Those skilled inthe art will appreciate that in this embodiment, the functions ofmodules 300 could be provided in modules other than those shown in FIG.3 . As an example, modules 300 can take the form of computer programcode stored in a non-transitory storage media 316 and executed by atleast one processor 320. Those skilled in the art will furtherappreciate that the various modules and/or functions 300 could bedifferently distributed across different processing devices, and thepresent invention is not limit by the particular distribution of suchmodules and/or functions shown in FIG. 3 .

FIG. 3 also shows an embodiment of a user device 340 that serves as adevice that enables a user (e.g., order selector) to interact with therobotic vehicle, e.g., to provide inputs. The user device 340 can bepart of, or onboard, robotic vehicle 130 or it can be a separate device,or some combination thereof. For example, user device 340 could be partof a control system on robotic vehicle 130 or it could be a handheldwireless device.

In some embodiments, the user device 340 is worn on a user. For example,in some embodiments, the user device 340 is worn on the user's head. Insome embodiments, the user device 340 is worn on the user's arm. In someembodiments, the user device 340 is worn on the user's wrist. In someembodiments, the user device 340 is worn on the user's hand.

In some embodiments, the user device 340 could be a device stationed ina zone or aisle or at a pick face. In other embodiments, the user device340 could be distributed across two or more of the robotic vehicles, ahandheld device, a stationary device in a zone or aisle or at a pickface, and a storage facility management system.

In some embodiments, the user device 340 comprises a communicationmodule 302. In some embodiments, the communication module 302 enablescommunication between the robotic vehicle 130 and external systems, suchas a storage facility management system 140 (e.g., a warehousemanagement system WMS 140), third party systems, remote service, and/orthe user device 340. The communication between these different systems,subsystems, and/or entities will be as described herein, but could bedifferent in other embodiments. Communication module 302 can enable oneor more known or hereafter developed types of communication, whetherwired or wireless, and implement the necessary protocols and messageformats associated therewith. Such types of communication can include,but are not limited to, Ethernet, Bluetooth, wireless modem/router, highspeed wire, radio frequency, and so on.

In some embodiments, the user device 340 comprises an order module 304.In some embodiments, the order module 304 can be used to receive anorder from WMS 140 or user device 340. That is, in some embodiments, WMS140 can receive an order from an external source, e.g., over theInternet, intranet, extranet, virtual private network (VPN), and so on,and communicate the order to robotic vehicle modules 300 viacommunication module 302. Otherwise, the order module 304 could receivean order from a non-transitory memory, such as a Flash drive, CD ROM, orsimilar storage device.

In some embodiments, user device 340 could be used to transmit an orderto robotic vehicle modules 300, via communication module 302. In FIG. 3, various input and output mechanisms are shown for a user device 340.These include a keypad or keyboard 349, input display (e.g., touchscreen) 342, and a voice input (e.g., microphone) 344, in thisembodiment. User device 340 could be a cell phone, personal digitalassistant, or similar network enabled, handheld device, as examples. Thedisplay can be any type of wired or wireless display. In someembodiments, the user device 340 does not include an input and/or outputmechanism.

Those skilled in the art will appreciate that the user device need notinclude all of the modules and/or components depicted in FIG. 3 . Inother embodiments, the user device could include a subset of the shownmodules and components, a different set of modules and components, or acombination thereof. As an example, in some embodiments, the user device340 can comprise one or more cameras, sensors, or the like. In someembodiments, the user device 340 can comprise one or more inertialmeasurement units.

When an order is received, or otherwise electronically stored at therobotic vehicle modules 300, a pick list module 306 can process theorder to generate a pick list. A pick list, therefore, is a list ofitems to be picked in the warehouse to fill at least one order. Inaddition to the order, the pick list module 306 can generate the picklist using various types of information, such as product inventory. Thepick list could also be generated using information relating to pickzones associated with products, and pick faces within pick zones wherethe products physically reside. Alternatively, a user may specify a picklist manually, e.g., via an interface on or off the robotic vehicle,such as the user interactive screens shown in FIGS. 4A-4B. Thisinformation can be stored in storage device 316, or be made availablefrom WMS 140. In some embodiments, the WMS 140 or other external systemcan provide a realized pick list, obviating the need for module 306.

With a pick list generated, a route module 308 can be used to generate aroute through the warehouse to be followed by robotic vehicle 130, asthe robotic vehicle works its way through the warehouse to gather theproducts. In addition to the pick list, route module 308 can generatethe route using various types of information, such as an electronic map318 representing the warehouse, including pick zones and pick faceswithin pick zones. In some embodiments, the electronic map 318 islocated at the robotic vehicle 130. In other embodiments the electronicmap 318 is located at the WMS 140, or at one or more other systems thatcommunicate with WMS 140 and/or robotic vehicle 130. In someembodiments, the electronic map 318 may reside at user device 340. Inthose embodiments in which the electronic map 318 is not at the roboticvehicle 130, route information is communicated to the robotic vehicle130.

As will be appreciated by those skilled in the art, the route module mayinclude functionality to optimize the route based on minimizing distancetravelled, minimizing congestion (in view of routes of other roboticvehicles), minimizing time, the known or estimated location of manuallyoperated equipment, and/or order stacking considerations (e.g., heaviestitems on bottom), as examples. The route can be stored in storage device316, or made available from WMS 140.

While order module 304, pick list module 306, route module 308, thenon-transitory storage media 316, and the at least one processor 320 areshown as part of robotic vehicle 130, in other embodiments one or moreof the foregoing could reside at the WMS 140, or at one or more othersystems that communicate with WMS 140 and/or robotic vehicle 130. Insome embodiments, one or more of these modules may reside at user device340.

Vehicle control system 135 is that system that generally causes roboticvehicle 130 to travel through the facility. It can receive instructions,and automatically route itself to a destination within a facility, e.g.a warehouse. Robotic vehicles can use electronic maps, markers, visionsystems, and so on for guidance. However, typical robotic vehicles haveno ability to iterate themselves through an environment (e.g., afacility), e.g., pausing or stopping at pick locations as described.

Vehicle control module 310 communicates with vehicle control system 135to achieve an iterative robotic navigation through an environment, inthis case warehouse 100. Vehicle control system 310 can use the routecreated by route module 308, which includes the pick zone and pick faceinformation necessary to fill the initial order. As will be described ingreater detail, vehicle control module 310 can cause vehicle controlsystem 135 to robotically navigate to a pick face within a pick zone.

In some embodiments, the robotic vehicle 130 comprises an input/output(I/O) manager 312. In some embodiments, the input/output (I/O) manager312 resides at the WMS 140, or at one or more other systems thatcommunicate with WMS 140 and/or robotic vehicle 130. In someembodiments, the input/output manager 312 may reside at user device 340.

In some embodiments, the input/output manager 312 communicates thepicking information to an order selector, e.g., that could ride on,walk-beside, follow, or meet the robotic vehicle, or may be stationed ata zone or pick face. The input/output manager 312 may include a voicecontroller 314. Display in module 342 and display out module 346 couldbe the same device, such as a touch screen. The output at the userdevice 340 could take the form of screens, and/or audio output via audioout module 348. The output could also include the output of lightpatterns, symbols, or other graphical or visual effects. In someembodiments, the output at the user device 340 takes the form of anaugmented reality device including, but not limited to, HoloLens and/orGlass. In some embodiments, the output at the user device 340 takes theform of a voice only device, such as a Vocollect belt pack and headset.

Once the items are picked, the user, by operating a user device, such asuser device 340, can indicate such to the robotic vehicle 130, via I/Omanager 312. For example, a user could simply say “Go” or “Next,” viaaudio in module 344, and vehicle control module 310 could cause thevehicle control system to navigate to the next stop in the route.Additionally, or alternatively, the user may be allowed to use a keypad349 or touch screen (display in module 342) entry to accomplish the sameaction.

In an alternative embodiment, the vehicle 130 includes sensors to trackthe weight of the goods loaded, and determine when the pick is completebased on the known weight of each case and the observed change in loadweight.

In some embodiments, the robotic vehicle 130 comprises one or moresensors configured to detect a user's gestures and/or gaze. In suchembodiments, the user could use a change in gesture and/or gaze toinstruct the robotic vehicle 130 to move to the next location.

In some embodiments, the user device 340 comprises one or more sensorsconfigured to detect a user's gestures and/or gaze. In such embodiments,the user could use a change in gesture and/or gaze to instruct therobotic vehicle 130 to move to the next location.

In some embodiments, the robotic vehicle 130 measures the weight of anitem loaded on the robotic vehicle 130. In such embodiments, the roboticvehicle 130 compares the weight measured with predetermined weightinformation for that item. If the measured weight matches thepredetermined weight, the robotic vehicle 130 determines that the itemhas been loaded. In some embodiments, the robotic vehicle 130 comparesthe items loaded to the pick list to determine when it is appropriate tomove to the next location.

In some embodiments, the robotic vehicle 130 measures the weight of anitem loaded on the robotic vehicle 130. In such embodiments, the roboticvehicle 130 compares the weight measured with predetermined weightinformation for that location. If the measured weight matches thepredetermined weight, the robotic vehicle 130 determines that the it isappropriate to move to the next location.

In the embodiments of FIGS. 4A and 4B, an approach to manually creatinga pick list by hand is shown. Here, Up, Down, Left, and Right keys areprovided to enable a user to choose specific pick faces to be includedin a pick list, which can be displayed via display out module 346. Eachpick face number represents a different pick face—where selection of apick face adds the pick face to the pick list.

Pick lists can be created in other ways in other embodiments. Forexample, an order could be entered and a pick list could beautomatically generated. The present disclosure is not limited to themanual approach of FIGS. 4A and 4B, nor is it limited to those screensor functionality.

FIG. 5 is a flowchart depicting an embodiment of a method 500 of pickingcases with robotic vehicle assistance, in accordance with aspects of thepresent disclosure. This method can be carried out by the roboticvehicle modules 300 of FIG. 3 , or similar systems. Method 500 can takeat least the following two forms:

-   -   Follow-Model with Button—Demonstrates the ability for a worker        (i.e., user or order selector) to team with a robotic vehicle to        travel a warehouse and pick an order without getting on or off a        pallet jack. The order selector can direct or control the flow        of the robotic vehicle.    -   Follow-Model with Voice Option—Complete hands-free operation of        a robotic vehicle to partner with an order selector to pick        cases can be provided. Here the order selector can be freed from        hands-on interaction with the robotic vehicle. The order        selector uses a voice system to command the robot        start/stop/slow down. The order selector directs or controls the        flow of the robotic vehicle and the voice system tells the order        selector what to do. In other embodiments, the order selector        could interact with the robotic vehicle using gestures, e.g.        hand signals.

As shown in FIG. 5 , a pick list can be entered into the robotic vehiclein step 510, and the order selector can initiate robotic vehicle travelto a first pick face in step 512. Robotic travel can be initiated byvoice, gesture, button or other user interactive mechanism. In step 514,the robotic vehicle navigates to the pick face. In step 516, the orderselector picks the products from the pick face. If the route iscomplete, step 518, the picked load is delivered, in step 520. The loadcould be delivered to a shipping and receiving area, a zone in thewarehouse, or some other designated location. If the route was notcomplete in step 518, the method returns to step 512, where the userinitiates robotic travel to the next pick face, or the robotic vehiclecould be dispensed to a next location, e.g., next pick face or loadingarea, through an onboard or external control signal.

FIG. 6 is a flowchart depicting an embodiment of a method 600 of pickingcases, in accordance with aspects of the present invention. This methodcan be carried out by the robotic vehicle modules 300 of FIG. 3 , orsimilar systems. Method 600 can take at least the following two forms:

-   -   Auto-Location Case Picking—A pre-programmed map of the warehouse        sets up each location as a distance grid and can be set as a        pause or slow down location for the robotic vehicle. For each        order, stops or slow downs are “Selected” based on the location        of the product on that order. The robotic vehicle travels        through the warehouse in a pre-determined path, stopping or        slowing where the order needs product. The order selector walks        along with the robotic vehicle and the system tells him when to        pick and what to pick. A command will tell the robotic vehicle        to go to the next location. In some embodiments, the robotic        vehicle 130 will slow down, cruise pass the pick face, then stop        just past it, if and only if the user had not completed the pick        by then. This allows picking of a small number of items without        stopping, but ensures the robot does not run away when there is        a large order. An extension of this could be to decide        pre-emptively to stop right at the pick face when more than X        items are to be picked.    -   WMS-Directed Location Case Picking—An order will be sent to a        robotic vehicle from the WMS 140. Based on the locations in that        order, the robotic vehicle will travel a “Smart Path” that is        created based on the order stops or slow-downs. The robotic        vehicle will travel to each location and stop or slow down for        work. This creates the flexibility to have the order selectors        follow the robotic vehicle or wait in pre-assigned zones for the        robotic vehicles to arrive for work, or be dynamically        dispatched to successive pick faces by a centralized system,        e.g., WMS 140.

As shown in FIG. 6 , a robotic vehicle can be provided with a maprepresenting the warehouse, in step 610. In step 612, a pick list isgenerated from an order. The pick list can be manually generated,computer generated, or some combination thereof. Pick faces aredetermined in step 614, and a route can be determined from the pickfaces, in step 616. Step 618 begins iterative guidance through thewarehouse. In step 618, navigation can be initiated by the user with acommand input to the robotic vehicle. The robotic vehicle navigates tothe next pick face based on the route and map.

In step 620, product is picked from the pick face, and loaded on therobotic vehicle, e.g., a pallet transport or tugger with cart. If, instep 622, the route is complete, the load can be delivered, in step 624,as described above. But if the route is not complete, the processreturns to step 618 for robotic navigation to the next pick face. Afterthe load is delivered the robotic vehicle can navigate to a stagingarea, in step 626.

FIG. 7 is a flowchart depicting an embodiment of a method 700 of pickingcases using zones and robotic vehicle assistance, in accordance withaspects of the present invention. This method can be carried out by therobotic vehicle modules 300 of FIG. 3 , or similar systems. Method 700can take at least the following form:

-   -   Zone Case Picking—The order selectors are assigned to strategic        zones (“pick zones”) that are dynamic enough to be changed in        order to balance productivity/capacity of the order selectors        and the capacity/utilization of the robotic vehicles. In some        embodiments, cases/hour rates can be set per zone to minimize        the amount of travel for different zones/order selectors based        on density for a certain area. The robotic vehicle will allow an        Ops Manager to set the zones for the day/time-period and the        robotic vehicles based on the volume for the day. The WMS 140        can assign orders to the robotic vehicles (or an operator can        scan in an order when pallets are loaded on the robotic vehicle)        and the order locations will be used to direct the robotic        vehicle where it needs to go. In some embodiments, robotic        vehicle modules 300 will optimize the path decision for the        robotic vehicle to get from location to location, as described        herein. The order selector can interact with each robotic        vehicle that arrives in a zone by logging into the “Robot Order”        or an auto-logon based on the zone the robotic vehicle is in, so        that the order selector can be directed via a voice or other        signal to pick a number of cases from the pick faces in that        zone. The robotic vehicle can be directed via a voice signal or        other signal to move onto the next zone. For example, such        signals could include a physical human gesture, a hands-on or        remote order selector input, or some other signal.

As shown in FIG. 7 , zones are defined within the warehouse 100, in step710, and the zones are staffed with order selectors in step 712. In step714, an order, pick list and/or route are loaded into the roboticvehicle. In step 716, the robotic vehicle navigates to a zone. An orderselector logs into an order, in step 718, either directly at the roboticvehicle or through an electronic device that communicates with therobotic vehicle either directly or through the WMS 140. In step 720, therobotic vehicle navigates to the first pick face in the zone. The orderselector loads the items in step 722. If picking within the zone is notcomplete, in step 724, the robotic vehicle navigates to the next pickface within the same zone, in step 726.

If, in step 724, picking in the zone is complete, a determination ismade of whether or not there is a next zone, in step 728. If so, therobotic vehicle goes to a next zone in step 730. If not, the roboticvehicle delivers the load, in step 732. After the load is delivered, therobotic vehicle could go to a staging area, as in step 734. For example,the robotic vehicle could go to a shipping and receiving area, as anexample, if the order is complete. In some embodiments, after the loadis delivered, the robotic vehicle could receive another order, picklist, and/or route.

In various embodiments described herein, the robotic vehicle has one ormore of the order, pick list and route locally stored. But in otherembodiments, one or more of the foregoing could be externally stored,e.g., at the WMS, and communicated to the robotic vehicle asneeded—perhaps just in time. For example, when an order selector loadsproduct from a pick face and is ready to initiate robot self-navigationto a next location, a voice or other input could cause the roboticvehicle to receive the next pick face location from the WMS or otherexternal system.

In accordance with aspects of the present invention, a variety of casepicking solutions are possible by including a robot control system infacility equipment, such as pallet transports, forklift, highlifts, andtuggers, to form a robotic vehicle. The resulting flexibility can beenhanced by interfacing the robotic vehicle with a storage facilitymanagement system to maximize the utilization of robotic vehicles tosupport a combination of factors that are important, in varying degrees,to each customer/facility. Balancing cases/hour with the labor costs andorders/hour may have different implications for efficiency and impactother areas, like put-away and shipping. There is great value in lettingeach facility balance its own people, processes and robots to achieveits own goals.

At the same time, the robot control system is flexible enough tointegrate with other technology in use at the warehouse. The robots takedirection from the WMS order, e.g., as orders are printed for thepickers, can follow an optimal path, and can display what to pick forthe worker on a screen mounted on the robot. The robots can arrive at azone and the worker can read the screen for what to pick. Additionally,or alternatively, the voice system can tell the worker what to pick. Nomatter the infrastructure and goals for that day and for that warehouse,the robot control system can be tuned on the fly to support the needs inreal-time. For instance, a warehouse can use label picking inperishables, voice in dry goods, and/or RF display in bulk, as examples.The robots can travel from location to location and the workers can beprompted via the method they are using.

In various embodiments, dynamic allocation and coordination ofauto-navigating vehicles can be a human-robot hybrid approach or arobot-robot approach to the problem of case (and possibly each) picking.Picking is the act of assembling an ordered group of goods from awarehouse in preparation for dispatching it to the customer. The type ofpicking referred to the above embodiments is case picking, where thegoods being picked are grouped in cases (e.g. a grocery warehouse, wherethe individual picks might be a case of 24 cans of soup, a large bag ofdog food, etc.), and assembled on a pallet for later transport. Dynamicallocation and coordination of auto-navigating vehicles can also applyto each picking, where smaller orders of individual items are gathered,such as customer orders from Amazon. This discussion will be framed interms of case picking, but dynamic allocation and coordination ofauto-navigating vehicles would be applicable in both scenarios invarious embodiments.

In traditional case picking, each selector (e.g., a human) is given apick list of cases that will make up a single outgoing pallet, generallysorted by aisle or by the order they need to go on the pallet (ifparticularly heavy or crushable cases are involved). They drive apowered pallet truck through the warehouse, incrementally assembling thepallet. Once complete, they take the pallet to the docks, get a new picklist, and repeat. There are a variety of inefficiencies in thisapproach, but the most significant is travel time: on average, selectorsspend 40-50% of their time simply moving from one pick location to thenext. While many warehouses organize popular products into a compactarea, there are nearly always a number of rarer items that require longtrips to acquire.

An alternative approach is zone picking, where the selectors remain(mostly) stationary near a zone of one (or multiple) bays of goods,picking cases onto a conveyor belt or other such mechanism. Thiseliminates long travel distances, but has a number of other challenges.If each selector is responsible for a small zone, they don't need tomove very far between picks, but risk being idle when nothing from theirlocations is needed. Increasing the zone size reduces idle time, butincreases walking time as they move back and forth. In addition, theupfront costs of the conveyor belts or other conveyance system aresignificant.

In various embodiments, dynamic allocation and coordination ofauto-navigating vehicles uses robotic pallet jacks and centrallydispatched roaming order selectors to create a significantly moreefficient, yet flexible, approach to picking. A dynamic allocation andcoordination of auto-navigating vehicles system receives the pick listsfrom the warehouse's inventory system (e.g. a WMS, WES, etc.). As picklists arrive, they are each assigned to an autonomous pallet jack, whichthen moves through the warehouse, akin to the manual selectors intraditional case picking, but without a human. When each robot reachesits next pick location, it comes to a stop and waits for a human to pickthe case. Humans are independently directed by the system, which makesdecisions about their next picks in real time. A number of factors aretaken into account, including travel time for the human, estimated timeof arrival to the next pick for each robot, potential sources ofcongestion, etc. This allows humans to be directed to a string of picks,often across many robots, without being tied to a specific zone of thewarehouse: a selector will move in a random walk through the entirewarehouse over the course of a shift. By using more robots than humans,the system is able to artificially increase the pick density ofslow-moving portions of the warehouse, as it can wait to send any humansuntil a critical mass of robots are in the area. Combined withcomputer-based methods to minimize human travel time, picking efficiencycan be greatly increased: in at least some environments, selectorstaffing can be halved.

FIG. 8 is a flowchart depicting an embodiment of a method 800 of pickingcases using dynamic allocation and coordination of auto-navigatingvehicles where order selectors are dynamically deployed to picklocations, in accordance with aspects of the present invention. Invarious embodiments, the assignment and movement of order selectors androbot vehicles to pick locations happens in parallel: an order selectorcan (and often will) begin moving to a pick location before the roboticvehicle has arrived.

FIG. 9 is a diagram of a warehouse 900 comprising a dynamic allocationand coordination of auto-navigating vehicles system 940 implementing themethod 800, in accordance with aspects of the present invention.

In various embodiments, a plurality of vehicles 130 are deployed tovarious pick faces where goods are selected and loaded on the vehiclesto fill orders. Order selectors 950 are also deployed to meet thevehicles 130 at the pick faces to select the goods and load the goods onthe vehicles. After such “picking,” the order selectors 950 can bedynamically redeployed to their next pick faces to select and load goodson the same or different vehicles. That is, in various embodiments,order selectors 950 are not dedicated to a particular pick location orvehicle 130. Rather, order selectors 950 are deployed based on analysisof locations of the order selectors 950 and next pick face locations ofthe vehicles 130. Additionally, or alternatively, in some embodiments,the order selectors 950 are deployed based on analysis of locations ofthe order selectors 950 and future pick face locations of the vehicles130. A dynamic allocation and coordination of auto-navigating vehiclessystem 940 is in communication with the order selectors 950, and canperform the analysis and orchestrate the deployment and redeployment ofthe order selectors 950, e.g., in real or near-real time. Thecommunication with the order selectors 950 is preferably wireless, usingany now known or hereafter developed wireless communication technology.The result is a highly efficient order selection process that minimizesthe idle time of order selectors.

In various embodiments, the system 940 can be located within thewarehouse 900 or external to the warehouse. Warehouse 900 can be similarto warehouse 100 of FIG. 1 . In various embodiments, the system 940 canform part of the warehouse management system 140. In variousembodiments, the vehicles 130 can be automated vehicles, semiautomatedvehicles, manned vehicles, and/or combinations of two or more thereof.In various embodiments, the order selectors 950 can be automatedvehicles, semiautomated vehicles, a human selector having a handhelddevice, and/or combinations of two or more thereof. In some embodiments,the order selectors 950 use a transport mechanism, such as, but notlimited to, a scooter, a powered vehicle, etc.

The communication from the system 940 to the order selectors 950 cantake the form of an electronic message received and processed by aprocessor of the order selectors 950. The electronic communication caninclude data and/or information identifying the next pick face for theorder selector. The data and/or information can identify the pick face,an identification of the good or goods to be picked, and/or a quantityof each good to be picked. In some embodiments, the electroniccommunication can include data and/or information that identifies therobotic vehicle 130 associated with the goods to be picked. In someembodiments, the data and/or information can include navigationinstructions to assist the order selector in navigating to the next pickface location. In the case of an automated or semiautomated orderselector (or order selector vehicle), the communication can beautomatically processed by the order selector to facilitate navigationto the next pick face location and picking of the appropriate goods.

In some embodiments, a human order selector can be equipped with ahandheld or mobile device (collectively “order selector” or “orderselector device”) that includes an order selector application configuredto process the communication. The order selector application caninterface with a navigation program and process the receivedcommunication to cause the device to output navigation instructions forproceeding to the next pick face location. The navigation instructionscan be output as text, a dynamically updated map of the facility, and/oraudio. That is, navigation instructions and outputs can be providedwithin the context of a map or other representation of the warehousefacility. The application can process the received communication todisplay images of the goods to be picked at the pick face, text, and/oroutput information identifying the goods to be picked. In someembodiments, the order selector application can include or interfacewith an application configured to read codes from packaging or labelingof the goods, e.g., a bar code scanner and/or QR code reader.

In some embodiments, the order selector can include one or more userinterface devices, including at least one pick-complete device that,when actuated, generates a pick-complete signal indicating that loadingof products from a pick location to the robotic vehicle has beencompleted and the robotic vehicle is clear to proceed to a new next picklocation on its route. For example, an order selector application on anorder selector device can be configured to electronically communicatethe pick-complete signal to the robotic vehicle 130, WMS 140, and/or thesystem 940.

Referring to the illustrative method 800 of FIG. 8 , which can beaccomplished by the system 940 of FIG. 9 , the process begins withassigning robotic vehicles to routes to fill orders in step 802, whichcan be accomplished by WMS 140. In step 804, the robotic vehiclesnavigate to next pick locations on their respective routes. Movement ofthe vehicles can be tracked, in step 806, e.g., by WMS 140 or anothertracking system, such as known tracking systems.

In step 808, locations of order selectors 950, vehicles 130, and nextpick locations of vehicles 130 are evaluated, e.g., by the system 940.In step 812 locations of the orders selectors 950 can be tracked. Basedon efficiency analysis by the system 940, next pick faces for the orderselectors are determined and the system 940 communicates a message tothe order selectors to deploy to service vehicles 950 at next picklocations, in step 810. In various embodiments, the order selectorsmovement occurs in parallel with robot motion, and order selectors maybe reassigned at any time.

The order selectors 950 meet vehicles 130 at next pick locations andload selected goods, in step 814. This step can include the orderselectors communicating to the robotic vehicle 103, WMS 140, and/or thesystem 940 that the pick is complete and the robotic vehicle 130 is freeto navigate to its next pick face location and the order selector isfree to be assigned to a next pick face location of the same or anotherrobotic vehicle. Translation of the order selectors 950 from one picklocation to the next is depicted by dashed arrows in FIG. 9 . Iffulfillment of all pick lists for each vehicle 130 is complete, in step816, the process can terminate. Otherwise, the process returns to step808 to continue to orchestrate deployment of order selectors 950 toselect and load goods from pick faces onto vehicles 130.

The analysis performed by the system 940 to efficiently deploy andredeploy the order selectors can take one or more various forms, e.g.,shortest routes, quickest routes, and so on, as described above.

In some embodiments, the analysis performed by the system 940 toefficiently deploy and redeploy the order selectors takes into accountthe fatigue level of at least one or the order selectors. In someembodiments, the analysis performed by the system 940 to efficientlydeploy and redeploy the order selectors is configured to maximizewarehouse throughput. In some embodiments, the analysis performed by thesystem 940 to efficiently deploy and redeploy the order selectors isconfigured to meet order shipment deadlines. In some embodiments, theanalysis performed by the system 940 to efficiently deploy and redeploythe order selectors is configured to maintain a maximum delay limit perorder (e.g. complete each order within a certain period after submissionof the order). In some embodiments, the analysis performed by the system940 to efficiently deploy and redeploy the order selectors is configuredto smooth facility output across the shift.

Beyond the broad strokes of dynamic allocation and coordination ofauto-navigating vehicles discussed above, there are a number ofincremental improvements that can be implemented within the system 940to further increase picking efficiency. Allowing the robots to coastpast the pick location, and stop just past it, allows small numbers ofcases to be picked onto the (slowly) moving robot, enabling it to speedback up without stopping after the pick is complete. Using a doublepallet jack and assigning two pick lists to each robot will alsoincrease overall pick density. This has been done with manual selection,but results in a significant number of cases placed on the wrong pallet:doing so effectively requires integration with the equipment to indicatewhich pallet is being picked to at a given time, a natural extension ofdynamic allocation and coordination of auto-navigating vehicles.Introducing another travel method for the selectors, such as industrialscooters, further boosts their efficiency.

Future improvements in the assignment algorithm can be used to reducethe need for faster selector travel, however. Finally, once the dynamicallocation and coordination of auto-navigating vehicles within the spacehas been more thoroughly explored, the goods in a warehouse could bere-slotted (rearranged) to optimize the locations of goods around thestrengths of the dynamic allocation and coordination of auto-navigatingvehicles. For instance, while concentrating fast-moving goods is helpfulfor manual selectors, it creates traffic jams, and the effects could beemulated in a more distributed fashion using dynamic allocation andcoordination of auto-navigating vehicles.

Other items that could be used to optimize the schedule around include,but are not limited to: deadlines for particular picklists, maintaininga maximum-delay limit per order (e.g. complete each order within X hoursof its submission, where X can be a parameter set via the WMS 140),managing order selector (e.g., human) fatigue levels, smoothing facilityoutput across the shift.

To date, the independent direction of robot pallet jack and human orderselectors equipped with order selector devices to perform a coordinated,distributed task of order fulfillment has not be conceived of andreduced to practice.

While the foregoing has described what are considered to be the bestmode and/or other preferred embodiments, it is understood that variousmodifications may be made therein and that the invention or inventionsmay be implemented in various forms and embodiments, and that they maybe applied in numerous applications, only some of which have beendescribed herein. It is intended by the following claims to claim thatwhich is literally described and all equivalents thereto, including allmodifications and variations that fall within the scope of each claim.

It will be understood that the inventive concepts can be defined by anycombination of the claims, regardless of the stated dependencies,wherein different combinations of claims can represent differentembodiments of the inventive concepts.

1. An electronic travel management method, comprising: providing amanagement system in communication with a plurality of robotic vehiclesand a plurality of mobile selector units, each robotic vehicle executinga route and each mobile selector unit having a wireless communicationdevice, wherein each route comprises a pick list identifying picklocations of items to be picked to fulfill an order; and the managementsystem orchestrating deployment and redeployment of the mobile selectorunits in real or near-real time with travel of the plurality of roboticvehicles, including: tracking locations and movement of the roboticvehicles along their respective routes; tracking locations of the mobileselector units; and directing the mobile selector units to futurelocations of the robotic vehicles based on locations of the roboticvehicles, routes of the robotic vehicles, and locations of the mobileselector units, wherein future locations of the robotic vehicles includefuture pick locations of the respective robotic vehicle routes.
 2. Themethod of claim 1, wherein routes of one or more of the plurality ofrobotic vehicles passes through a plurality of pick zones and the methodincludes confining travel of at least one of the mobile selector unitsto a subset of the plurality of pick zones.
 3. The method of claim 1,wherein routes of one or more of the plurality of robotic vehiclespasses through a plurality of pick zones and the method includesconfining travel of at least one of the mobile selector units to one ofthe plurality of pick zones.
 4. The method of claim 1, wherein directingthe mobile selector units to future locations of the robotic vehiclesincludes communicating navigation instructions to at least one of themobile selector units.
 5. The method of claim 4, further comprisingoutputting the navigation instructions to at least one of the mobileselector units as text, a dynamically updated map of the facility,and/or audio.
 6. The method of claim 4, further comprising outputtingthe navigation instructions within the context of a map or otherrepresentation of a warehouse facility.
 7. The method of claim 1,wherein orchestrating travel further comprises automatically performingcongestion avoidance analysis based on locations of one or more of themobile selector units and locations and/or next pick locations of one ormore of the plurality of robotic vehicles.
 8. The method of claim 7,further comprising directing travel of one or more of the plurality ofrobotic vehicles based, at least in part, on the congestion avoidanceanalysis.
 9. The method of claim 7, further comprising directing travelof one or more of the mobile selector units based, at least in part, onthe congestion avoidance analysis.
 10. The method of claim 7, furthercomprising directing travel of one or more of the mobile selector unitsand one or more of the plurality of robotic vehicles based, at least inpart, on the congestion avoidance analysis.
 11. The method of claim 7,further comprising performing the congestion avoidance also based onother potential sources of congestion including humans, other vehicles,hazards, mobile equipment, and/or a dynamically updated map.
 12. Themethod of claim 7, further comprising performing the congestionavoidance also based on other travel speeds of the one or more of themobile selector units and/or the one or more of the plurality of roboticvehicles.
 13. The method of claim 7, further comprising performing thecongestion avoidance also based on routes of the one or more of theplurality of robotic vehicles.
 14. The method of claim 1, wherein theplurality of robotic vehicles includes an autonomous forklift,high-lift, and/or pallet truck.
 15. The method of claim 1, wherein oneor more of the mobile selector units take the form of a handheld mobileterminal.
 16. The method of claim 1, wherein one or more of the mobileselector units take the form of a mobile phone or tablet.
 17. The methodof claim 1, wherein one or more of the mobile selector units take theform of a vehicle-based mobile terminal.
 18. The method of claim 1,wherein orchestrating travel further comprises reducing travel distancesand/or travel times of the mobile selector units and/or the roboticvehicles.
 19. The method of claim 1, wherein orchestrating travelfurther comprises dynamically determining and wirelessly communicatingnext navigation instructions to the plurality of mobile selector unitsbased, at least in part, on changes in the locations of the mobileselector units and/or the robotic vehicles.
 20. The method of claim 1,wherein one or more of the mobile selector units is a mobile selectorrobot.